ࡱ>  NOY ˂bjbjWW E==T|s]_^_^  [![![!t!!!!!T#"!, >=, <=, <>, like and not like) and a  Figure 2: Result table from querying SIMULATION table. text entry which can include wildcards. The operator is selected from a drop down list. Sample values for the text entry are also available in a drop down list. We provide these features to minimise two of the major problems inherent in text based query languages, such as SQL. These are a semantic one in choosing the correct attributes and relationships between them, and a syntactic one in building the correct textual expression that corresponds to the chosen query. By offering the user choices of column names, table names and operators, the instance of syntactic error can be reduced. Providing column names and sample values can aid substantially in narrowing the semantic meaning of a domain [13]. For example, a column called TITLE in a personnel database could be used to store values such as Mr, Mrs, Dr, etc., or it could store a persons job title such as Chief Engineer. A sample value will quickly clarify the intended meaning. Our interface randomly selects ten sample values to be displayed for each simple attribute type. The drop-down list of samples displays the SQL-type by default as this also provides useful information. The table names, column names, data types and sample values used in the query form are obtained from the XUIS used to initialise the system. When the user submits a query to the database a result page is returned to the user in the form of a table whose columns are the marked fields and whose rows are the data items that satisfy any restrictions entered. Users familiar with the structure of a database can get answers to particular queries using the query mechanism alone. However we also provide a convenient data browsing mechanism. 2.3.2 Browsing After a result table is returned from the initial searching step the user is in browsing mode. Figure 2 shows a sample result table after performing a query on the SIMULATION table in the schema of Figure 3. In this mode the user may examine the table, print or save the data, scroll backward and forward through the pages returned from the database, or browse related information. Figure 2 shows that the SIMULATION result table contains data corresponding to simple SQL-types, such as the title and date for a simulation. It also contains a number of hypertext links from the SIMULATION_KEY, DESCRIPTION and AUTHOR_KEY columns. Our interface automatically inserts several different types of link that we describe below. The SIMULATION result table (figure 2) displays a link on each AUTHOR_KEY attribute. This is because AUTHOR_KEY is a foreign key in the SIMULATION table that references the AUTHOR table (see Figure 3). Selecting a link on an AUTHOR_KEY value will retrieve full details of the author by displaying the appropriate row from the AUTHOR table. Since a primary key occurs exactly once in its table, following a foreign key link returns a single row. The inverse relationship provides a primary key link to a table in which the primary key value appears as a foreign key. Since a foreign key may occur any number of times in a table, following a primary key link may change the number of rows in the table returned to the user. Also because primary keys may appear in several tables as a foreign key, there may be a choice of tables to browse to. Referring to Figure 3, SIMULATION_KEY is the primary key of the SIMULATION table. SIMULATION_KEY links to three tables where it appears as a foreign key; the RESULT_FILE table, CODE_FILE table and VISUALIATION_FILE table. Each individual SIMULATION_KEY value of Figure 2 therefore contains a primary key link. Selecting one of these values will return all the rows that the key appears in from one of the referenced tables. The particular table is indicated in the currently checked radio button in the column header. Figure 3: Sample database schema for UK Turbulence Consortium. The table of data returned by our software interface may be quite large. Cells associated with simple values, such as numbers or short character strings, display the actual values. As well as simple types, we also use BLOB and CLOB types, to store small files that can be uploaded over the Internet. Cells associated with these types display a LOB link to the object. Clicking on such a link causes the data associated with the cell to be rematerialised and returned to the client. The link displays the size of the object in bytes, which may help users decide whether they want to retrieve the object. For example, Figure 3, indicates that the DESCRIPTION attribute in the SIMULATION table is a CLOB type. Selecting this link will retrieve the description and display it directly in the browser window since it contains character data. For binary data (e.g. a stored image or executable) selecting the link will allow the user to retrieve the data as a file. The sample schema of Figure 3 also contains three attributes of the DATALINK SQL-type. These DATALINK attributes serve the main purpose of our architecture to archive large scientific data via the web. The attributes in the Turbulence Consortium schema of Figure 3 are used for storing result files, code files, and visualisation files. These values are displayed as a filename in a result table, with a hypertext link that contains an encrypted key, required to access the file from the remote file server. This key is explained in more detail in section 2.4. All of the link types that are described above are generated automatically in our system from information contained in the XUIS. This indicates which columns are of the BLOB, CLOB and DATALINK type and also contains details of primary key to foreign key relationships. A default XUIS will automatically contain these relationships if referential integrity constraints have been defined in a database. However, during customisation of the XUIS it is possible to add relationships between tables, for browsing purposes, even if the database does not specify these constraints. 2.4 SQL/MED: The New DATALINK Type Both ANSI and ISO have accepted the proposal for SQL Part 9: Management of External Data [4], which includes the specification of the DATALINK type. ISO progressed SQL/MED from working draft to committee draft in December 1998. If things go according to schedule it should become a standard in late 2000. DATALINKs provides the following features for database management of external files: Referential Integrity An external file referenced by the database cannot be renamed or deleted. Transaction Consistency Changes affecting both the database and external files are executed within a transaction. This ensures consistency between a file and its metadata. Security File access controls can be based on the database privileges. Coordinated Backup and Recovery The database management system can take responsibility for backup and recovery of external files in synchronisation with the internal data. Our interface uses IBMs implementation of the DATALINK type [14, 15] that is available for DB2 version 5.2. We used the version of this software available for IBMs AIX operating system. This uses a DB2 database that stores the data associated with standard types internally, plus DATALINK specific software running on the remote file servers to manage external data. This software processes SQL INSERT, UPDATE and DELETE statements that affect DATALINK columns, to link and unlink files for the database. It manages information about linked files, and previous versions of linked files for recovery purposes. It also intercepts file system commands to ensure that registered files are not renamed, deleted and optionally, check the users access authority. An example of the SQL syntax for creating a table with a column containing a DATALINK SQL-type is given below (refer to the RESULT_FILE table in the schema of Figure 3): CREATE TABLE RESULT_FILE ( download_result DATALINK LINKTYPE URL FILE LINK CONTROL READ PERMISSION DB RECOVERY yes, file_name VARCHAR(150) NOT NULL, file_size_byte INTEGER, The LINKTYPE URL parameter indicates that values stored in the DATALINK column are specified using URL syntax. This has the advantage of identifying the remote file server host, directory structure and filename. The FILE LINK CONTROL parameter specifies that a check should be made to ensure the existence of the file during a database insert or update. Read permission can be set to DB (database) of FS (filesystem). If the database manages read permission then files can only be accessed using an encrypted file access token, obtained from the database by users with the correct database privileges. Without a valid token, the DATALINK software denies the read request. The RECOVERY yes parameter indicates that the DATALINK software coordinates backup and recovery between the referenced files and the database. Further details of these parameters, and additional parameters that can be specified in the DATALINK column definition, are available in [4]. A DATALINK value can be entered via a standard SQL INSERT or UPDATE statement. The value takes the form:  HYPERLINK http://host/filesystem/directory/filename http://host/filesystem/directory/filename The filesystem part of this URL is a specially mounted DATALINK File System (DLFS) in our AIX version of the software. The directory and filename are standard UNIX file systems. If read permission is managed by the database, an SQL SELECT statement retrieves the value in the form:  HYPERLINK http://host/filesystem/directory/filename http://host/filesystem/directory/access_token;filename The file can then be accessed from the filesystem in the normal way using the name: access_token;filename or, by using the full URL if the file is placed on a web server (as in our system). The access tokens have a finite life determined by a database configuration parameter. This can be set to expire after an interval set in seconds. Future Work 3.1 Processing of Data Files Prior to Retrieval An advanced customisation feature we are implementing is the ability to associate operations with SQL data types, or database attributes, through modification of a new operation element in the XUIS. An operation can, for example, allow a post-processing code (stored internal or external to the database, as a BLOB or DATALINK value) to be associated with a database column that stores arrays of simulation data (as a DATALINK). The post-processing code then provides additional interface functionality, such as array slicing and visualisation, for the data contained in this attribute. 3.2 Federated Database Access Our system can be modified to provide a multidatabase language system (in the taxonomy by Bright et al. [16]) in which heterogeneous databases can be accessed at the user interface level through a query language and tools that can integrate data from different sources without a global schema. We are implementing this functionality by extending the DTD for the XUIS to contain multiple database user interface definitions. The relationships, which currently allow browsing of related data in associated tables, will be extended to allow browsing to related data in tables in disjoint databases. Queries can be shipped to remote database using JDBC drivers that operate over networks. As well as FDB browsing a new element will allow several tables to be grouped into a supertable. A supertable will present a single view of the grouped tables for query purposes. Columns that participate in the supertable will be limited to columns assigned the same alias name in the XUIS. This FDB functionality, although limited, will serve a useful purpose of allowing not only distribution of result files, but also distribution and autonomous administration of the database containing the simulation metadata stored internally in the database. Conclusions We have constructed a prototype system to meet a requirement of the UK Turbulence Consortium to make available to authorised users, large result files from numerical simulations, with a total storage requirement in the hundreds of gigabyte range. Our interface is specifically aimed at users with a scientific background who are not familiar with SQL. As such, we aim to help users locate scientific data files of interest, using an intuitive searching and browsing mechanism in keeping with a web-based look and feel. One of the implications of this is that we automate the interface construction so that it requires little database or web development experience to install and access. This is a generic, schema-driven system that can be used to manage many different types of large, distributed data archives. We achieve the automated construction by allowing the user interface specification to be defined in an XML file used to initialise the system and by providing a tool that can generate a default XML specification. Separating the user interface specification from the user interface processing can provide a number of further advantages: The user interface, although schema driven, can be customised to use aliases for table and column names and to present different sample values. Hypertext links to related data can be specified in the XML even if there are no referential integrity constraints defined for the database. Different Users (or classes of user) can have different XML files thereby providing them with different user interfaces to the same data. Our architecture uses distributed commodity computing, that combines the new SQL DATALINK type, defined in SQL/MED, with a web-based interface to the data. This architecture provides web access to large, distributed files but maintains database security, integrity and recovery. As far as we are aware, this is the first use of this technology for web-based scientific data archiving. Bandwidth is a limiting factor in our environment. We greatly reduce bandwidth requirements by avoiding costly network transfers associated with uploading data files to a centralised site. Data distribution also reduces retrieval bottlenecks at individual sites. Post-processing of data files can further reduce the bandwidth requirements of file retrieval. Our on-going work is exploring ways to extend the XML user interface specification to allow operations to be specified for database columns, so that a user can extend the interface by including post-processing codes. These codes can then be applied dynamically to the data on the file servers to reduce the volume of data being returned. Finally, extensions are being implemented to define access to autonomous databases in a loosely coupled multidatabase environment. Acknowledgements The UK Turbulence Consortium (EPSRC Grant GR/M08424) provided data for this project. IBMs DB2 Scholars programme provided us with DB2 licenses. The DB2 Data Protection and Recovery Team at IBM were extremely helpful when responding to technical questions regarding DB2s DATALINK implementation. References [1] Sandham, N.D. and Howard, R.J.A. Direct Simulation of Turbulence Using Massively Parallel Computers. In: A. Ecer et al., eds. Parallel Computational Fluid Dynamics '97, Elsevier, 1997. [2] Williams, R., Bunn, J., Reagan, M., and Pool, C., T. Workshop on Interfaces to Scientific Data Achives, California, USA, 25-27 March, 1998, Technical Report CACR-160, CALTECH, 42pp.  HYPERLINK http://www.cacr.caltech.edu/isda http://www.cacr.caltech.edu/isda [3] Eisenberg, A. and Melton, J., SQL:1999, formerly known as SQL3, SIGMOD Record, 28(1), March, 1999. [4] Mattos, N., Melton, J. and Richey, J. Database Language SQL-Part 9:Management of External Data (SQL/MED), ISO/IEC Committee Draft, CD 9075-9 (ISO/IEC JTC 1/SC 32 N00197), December, 1988.  HYPERLINK ftp://jerry.ece.umassd.edu/isowg3/x3h2/1997docs/ ftp://jerry.ece.umassd.edu/isowg3/dbl/YGJdocs/ ygj023.pdf [5] Extensible Markup Language (XML) 1.0, W3C Recommendation, 10 February, 1998. http://www.w3.org/TR/REC-xml [6] Zloof, M., M. Query By Example. American Federation of Information Processing (AFIPS) Conf. Proc., Vol. 44, National Computer Conference, 1975, 431-8. [7] Manber, U. Future Directions and Research Problems in the World Wide Web. Proc ACM SIGMOD Conf., Montreal, Canada, June 3-5, 1996, 213-15. [8] Warren, M., S., et al. Avalon: An Alpha/Linux Cluster Achieves 10 Gflops for $150k. Gordon Bell Price/Performance Prize, Supercomputing 1998. http://cnls.lanl.gov/avalon/ [9] Sheth, A., and Larson, J. Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases. ACM Computing Surveys, Vol. 22(3), 1990, 183-236. [10] Davidson, J., D., and Ahmed, S. Java Servlet API Specification, Version 2.1a, November, 1988. http://java.sun.com/products/servlet/index.html [11] White, S., Hapner, M. JDBC 2.0 API, Sun Microsystems Inc., Version 1.0, May, 1998. http://java.sun.com/products/jdbc/ [12] Catarci, T., Costabile, M., F., Levialdi, S., and Batini, C. Visual Query Systems for Databases: A Survey. Journal of Visual Languages and Computing, 8, 1997, 215-60. [13] Haw D., Goble, C., A., and Rector, A., L. GUIDANCE: Making it easy for the user to be an expert. Proc. of 2nd International workshop on User Interfaces to Databases, Ambleside, UK, 13-15th July, 1994, 19-44. [14] Quick Beginnings, IBM DB2 File Manager for AIX, Version 5.2. Part Number 04L6231, IBM Corporation, 1998, 85pp. [15] Davis, J., R. DATALINKS: Managing External Data with DB2 Universal Database, White paper, IBM Corporation, August, 1997.  HYPERLINK http://www.software.ibm.com/data/pubs/papers/ http://www.software.ibm.com/data/pubs/papers/ [16] Bright, M., W., Hurson, A., R., and Pakzad, S., H. A taxonomy and Current Issues in Multidatabase Systems. IEEE Computer, 25(3), 1992, 50-60.  A 576 processor Cray T3E-1200E situated at the University of Manchester, which forms part of the Computer Services for Academic Research (CSAR) service run on behalf of the UK research Councils. http://www.csar.cfs.ac.uk/  We use the definition of loosely coupled FDBS by Sheth and Larson [9] to mean that there is no central administration in terms of creation of, and access to, the data.  A demonstration system is available at URL http://www.hpcc.ecs.soton.ac.uk/~turbulence/database. Login with username and password both equal to guest. The guest account has the limitation that data files cannot be downloaded. 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